1. Field of the Invention
The present invention generally relates to audience statistics, and more specifically to methods and systems for computing statistics relating to station audiences, particularly terrestrial radio stations.
2. Description of the Related Art
Radio ratings are very important to many different divisions of a radio station company, including radio station executives, advertising and marketing departments, and program directors. Radio station executives use ratings statistics to help them evaluate the health of the company's radio stations, as well as monitoring competitors and industry-wide trends. Advertisers and marketers depend on ratings to measure the effectiveness of their advertising/marketing strategies and adapt to changing market environments and fads. It is a program director's responsibility to not only have an intimate understanding of how ratings are compiled and calculated, but also how to utilize these ratings in an effort to adapt and innovate software solutions for varying market circumstances and business needs.
There are several standard types of statistics (ratings data) for researching radio stations, including AQH (or AQHP), Cume, and primary demographic. AQH stands for Average Quarter Hour (AQHP is Average Quarter Hour Persons), and refers to the average number of people listening to a radio station for at least five minutes in any quarter hour of a radio station's schedule. The number of people listening to an entire hour is not necessarily the sum of four quarter hours because of duplication. However, some people may listen for more than a single quarter hour. Cume is the total number of different (unique) persons that listen to a radio station within a given daypart. A daypart is a set of times throughout a given week. For example, a daypart could be every weekday (Monday through Friday) from 6:00 am until 10:00 am. If the daypart is 15 minutes there is no difference between AQH and Cume. Primary demographic refers to various categories of consumers (listeners of a given radio station) such as gender or age.
Arbitron, Inc., is an organization which collects raw radio listener data and generates statistical information similar to the standard statistics mentioned above. It is a media and marketing research firm which primarily serves media companies and advertisers/advertising agencies who carry out ratings analysis based on the statistics. Arbitron selects random samples of the population throughout various metro areas in the United States, and participants keep a diary of their actual listening times. Respondent-level data (RLD) is the raw data collected by Arbitron, while the summary data set (SDS) is the various statistics calculated by Arbitron, which is derived from the respondent-level data and has only specifically-selected dayparts (40 dayparts total).
Tapscan is a local market radio ratings software suite developed by Arbitron, which is used by media planners (e.g., ad agencies) to decide where to place their clients' radio commercials. Some of the specific features of Tapscan include ranking radio stations based on their broadcast hours, day, audiences, etc., using audience composition data (consumer demographics) to determine which radio stations are listened to by what people, presenting cost and radio station data in different ways, providing access to customized demographics, geographies, dayparts and multibook averages, and determining a radio station's reach and frequency by specific demographic, daypart, and spot level. Tapscan uses RLD and SDS, and other data sets such as Arbitron's Black Radio Data, Hispanic Radio Data, and Eastlan Radio Data.
Although Tapscan and other radio station ratings programs can provide a reach value for a radio station, the reach provided is calculated based on interpretation of listener statistics. Those interested in radio station research might find a different source of reach useful, as well as other statistics which are related to reach. The values of such statistics as AQH and Cume provided by Arbitron are calculated using a limited set of dayparts, which means that these values would be different if an alternative set of dayparts was defined.
It would, therefore, be desirable to devise an improved method of calculating ratings data for radio stations. It would be further advantageous if the method could effectively approximate different ratings statistics from previously collected data for arbitrary user-specified schedules.